The compressibility of stationary random processes

Author

McCoy ; Magotra, J.W. ; Stearns, N.T.

Author_Institution

Dept. of Electr. Eng. & Comput. Eng., New Mexico Univ., Albuquerque, NM

Volume

5

fYear

1996

fDate

7-10 May 1996

Firstpage

2527

Abstract

There are two types of inefficiencies in the time domain representation of a digitized random process. One is the time correlation between samples that causes one sample to be predictable based on the previous samples. Another is the non-uniform distribution of sample amplitudes. Maximum lossless compression of a stationary random process occurs when a sequence is completely decorrelated without loss and the decorrelated sequence is encoded at its entropy rate. This paper presents a mathematical description of theoretical limit of the compressibility of Gaussian stationary random processes

Keywords

Gaussian processes; autoregressive moving average processes; correlation methods; data compression; encoding; entropy; random processes; signal representation; signal sampling; time-domain analysis; ARMA process; Gaussian stationary random processes; digitized random process; encoded decorrelated sequence; entropy rate; maximum lossless compression; nonuniform distribution; sample amplitudes; stationary random processes compressibility; time correlation; time domain representation; Decorrelation; Equations; Filtering; Filters; Linear systems; Noise level; Power generation; Power system modeling; Random processes; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on

Conference_Location

Atlanta, GA

ISSN

1520-6149

Print_ISBN

0-7803-3192-3

Type

conf

DOI

10.1109/ICASSP.1996.547978

Filename

547978